How does the Internet of Things (IoT) help in microalgae biorefinery?

Wang K 1 , Khoo KS 2 , Leong HY 3 , Nagarajan D 4 , Chew KW 5 , Ting HY 6 Show all authors , Selvarajoo A 7 , Chang JS 8 , Show PL 9

Affiliations 

  • 1 Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia; College of Food Science and Engineering, Food Safety Laboratory, Ocean University of China, Qingdao 266000, China
  • 2 Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
  • 3 Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China. Electronic address: leong.hy@zju.edu.cn
  • 4 Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan 701, Taiwan
  • 5 School of Energy and Chemical Engineering, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan, Malaysia; College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, Fujian, China. Electronic address: kitwayne.chew@xmu.edu.my
  • 6 Drone Research and Application Centre, University College of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia. Electronic address: alan.ting@ucts.edu.my
  • 7 Department of Civil Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia. Electronic address: Anurita.Selvarajoo@nottingham.edu.my
  • 8 Department of Chemical Engineering, National Cheng Kung University, Tainan 701, Taiwan; Department of Chemical and Materials Engineering, Tunghai University, Taichung 407, Taiwan; Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung 407, Taiwan. Electronic address: changjs@mail.ncku.edu.tw
  • 9 Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia. Electronic address: PauLoke.Show@nottingham.edu.my
Biotechnol Adv, 2021 Aug 25.
PMID: 34454007 DOI: 10.1016/j.biotechadv.2021.107819

Abstract

Microalgae biorefinery is a platform for the conversion of microalgal biomass into a variety of value-added products, such as biofuels, bio-based chemicals, biomaterials, and bioactive substances. Commercialization and industrialization of microalgae biorefinery heavily rely on the capability and efficiency of large-scale cultivation of microalgae. Thus, there is an urgent need for novel technologies that can be used to monitor, automatically control, and precisely predict microalgae production. In light of this, innovative applications of the Internet of things (IoT) technologies in microalgae biorefinery have attracted tremendous research efforts. IoT has potential applications in a microalgae biorefinery for the automatic control of microalgae cultivation, monitoring and manipulation of microalgal cultivation parameters, optimization of microalgae productivity, identification of toxic algae species, screening of target microalgae species, classification of microalgae species, and viability detection of microalgal cells. In this critical review, cutting-edge IoT technologies that could be adopted to microalgae biorefinery in the upstream and downstream processing are described comprehensively. The current advances of the integration of IoT with microalgae biorefinery are presented. What this review discussed includes automation, sensors, lab-on-chip, and machine learning, which are the main constituent elements and advanced technologies of IoT. Specifically, future research directions are discussed with special emphasis on the development of sensors, the application of microfluidic technology, robotized microalgae, high-throughput platforms, deep learning, and other innovative techniques. This review could contribute greatly to the novelty and relevance in the field of IoT-based microalgae biorefinery to develop smarter, safer, cleaner, greener, and economically efficient techniques for exhaustive energy recovery during the biorefinery process.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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